Tags:

This strategy is a breakout strategy based on the price momentum indicator MACD and moving average, suitable for 1-hour timeframe on silver (XAG/USD, XAG/EUR). The key is to combine price trends and momentum indicators to determine the timing of trend reversals.

When the MACD histogram changes from negative to positive and continuously breaks through the signal line, it indicates that the short-term uptrend is stronger. At the same time, if the closing price breaks through the rising trend of the moving average, it generates a long signal. Similarly, when the MACD histogram changes from positive to negative and falls below the signal line, and the closing price falls below the downward trend of the moving average, it generates a short signal.

Specifically, the conditions for determining the long entry signal of this strategy are:

- The MACD histogram is positive
- The current histogram bar is higher than the previous one
- The closing price is higher than the moving average
- The closing price is higher than the highest price of the recent 3 K-lines

The conditions for determining the short entry signal are just the opposite.

Once the position is opened, it is closed unconditionally when the next K-line closes. This strategy does not set profit taking or stop loss points, aiming to capture the starting point of trend outbreaks.

This strategy combines price and momentum indicators to determine the timing of trend reversals more accurately with a higher winning rate. The way of unconditional closing in the next K line can effectively avoid the loss again after the reversal fails.

No setting of profit taking and stop loss meets the needs of investors pursuing high returns.

Lack of stop loss can easily lead to loss fixation and higher risk of loss. If the reversal signal fails, loss may mount due to the inability to stop loss in time.

The way of unconditional closing in the next K line makes it difficult to continuously capture trend profits.

It’s possible to consider adding appropriate stop-loss strategies on the basis of high-win breakthrough buys to reduce risk of loss.

It’s also possible to combine advanced techniques to re-enter positions after closing, attempting to continuously capture trend profits.

In general, this strategy belongs to an aggressive high-risk strategy. Due to no stop loss setting, investors need to bear greater risk of loss. But if the reversal is successful, the opportunity to open positions with full lots in the first place can also result in high returns. It is suitable for aggressive investors with relatively strong psychological endurance.

/*backtest start: 2023-01-31 00:00:00 end: 2024-01-13 05:20:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ // This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/ // © SoftKill21 //@version=4 strategy("XAG strategy 1h",overlay=true) fromDay = input(defval = 1, title = "From Day", minval = 1, maxval = 31) fromMonth = input(defval = 1, title = "From Month", minval = 1, maxval = 12) fromYear = input(defval = 2020, title = "From Year", minval = 1970) var gica = 0 var marcel = gica+2 //monday and session // To Date Inputs toDay = input(defval = 31, title = "To Day", minval = 1, maxval = 31) toMonth = input(defval = 12, title = "To Month", minval = 1, maxval = 12) toYear = input(defval = 2020, title = "To Year", minval = 1970) startDate = timestamp(fromYear, fromMonth, fromDay, 00, 00) finishDate = timestamp(toYear, toMonth, toDay, 00, 00) time_cond = true len = input(10, minval=1, title="Length") src = input(close, title="Source") out = sma(src, len) //distanta = input(1.004) fast_length = input(title="Fast Length", type=input.integer, defval=12) slow_length = input(title="Slow Length", type=input.integer, defval=26) signal_length = input(title="Signal Smoothing", type=input.integer, minval = 1, maxval = 50, defval = 9) sma_source = input(title="Simple MA(Oscillator)", type=input.bool, defval=false) sma_signal = input(title="Simple MA(Signal Line)", type=input.bool, defval=false) // Plot colors col_grow_above = #26A69A col_grow_below = #FFCDD2 col_fall_above = #B2DFDB col_fall_below = #EF5350 col_macd = #0094ff col_signal = #ff6a00 // Calculating fast_ma = sma_source ? sma(src, fast_length) : ema(src, fast_length) slow_ma = sma_source ? sma(src, slow_length) : ema(src, slow_length) macd = fast_ma - slow_ma signal = sma_signal ? sma(macd, signal_length) : ema(macd, signal_length) hist = macd - signal option1=input(true) option2=input(true) long2 = close > open and time_cond and close > out and hist > 0 and hist > hist[1] short2 = close < open and time_cond and close < out and hist < 0 and hist < hist[1] long1 = (close > open ) and time_cond and close > out and hist > 0 and hist > hist[1] and high > high[1] and high[1] > high[2] and close > high[1] and close > high[2] and close > high[3] short1 = (close < open) and time_cond and close < out and hist < 0 and hist < hist[1] and low < low[1] and low[1] < low[2] and close < low[1] and close < low[2] and close < low[3] if(option1) strategy.entry("long",1,when= short1) strategy.entry("short",0,when=long1) strategy.close_all() if(option2) strategy.entry("long",1,when= short2) strategy.entry("short",0,when=long2) strategy.close_all() // if(strategy.openprofit < 0) // strategy.close_all() // if(strategy.openprofit>0) // strategy.close("long",when = close < open ) // strategy.close("short",when = close > open) // strategy.close("long",when= close < open) // strategy.close("short",when= close> open) // tp = input(0.0003) // sl = input(0.005) // strategy.exit("closelong", "long" , profit = close * tp / syminfo.mintick, loss = close * sl / syminfo.mintick, alert_message = "closelong") // strategy.exit("closeshort", "short" , profit = close * tp / syminfo.mintick, loss = close * sl / syminfo.mintick, alert_message = "closeshort")

- Single Point Moving Average Breakout Strategy
- Moving Average Crossover Strategy
- SuperTrend Strategy
- Parabolic Period and Bollinger Band Combined Moving Stop Loss Strategy
- Moving Average Price Based Trading Strategy
- Ergotic Momentum Direction Convergence Trading Strategy
- Moving Average and Stochastic Trading Strategy
- An Optimization of Dual Moving Average Trend Following Strategy Based on Indicators Combination
- The Efficient Quant Trading Strategy Combining
- Dual Moving Average Crossover and Williams Indicator Combo Strategy
- RWI Volatility Contrarian Strategy
- Parabolic SAR Trend Tracking Stop Loss Reversal Strategy
- Momentum Indicator Crossover Strategy
- Efficient Oscillation Breakthrough Dual Stop Profit and Stop Loss Strategy
- Dual Channel Breakout Strategy
- Grid Trading Strategy Based on Real-time K-line Tracking
- Breakout Pullback Strategy
- Multi-cycle Adaptive Trend Forecast Strategy
- Renko ATR Trend Reversal Strategy
- Ichimoku Clouds Quant Strategy